Modulation effect with global ambiguity in 2-dimensional random walk

Tomoko Sakiyama; Yukio Gunji

doi:10.1063/1.4912818

Modulation effect with global ambiguity in 2-dimensional random walk

Tomoko Sakiyama, Yukio Gunji

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Here, we developed 2-dimensional multi agent random walk algorithm. In our algorithm, agents interact with each other and change their directional rules by detecting other agents' moving direction locally. In addition to that, modulation effects in which agents control rule intervals depending on amount of local other agents are equipped to our model. We show that modulation effects which introduce global ambiguity play a crucial role to establish optimal random walk by checking the slope value (μ) depending on dense of agents. We set modulation-added model and non-modulation model. The latter is control model. In case of non-modulation model, the slope values (μ) highly depends on dense of agents. However, in case of modulation-added model, the slope values (μ) are flexible and independent from dense of agents.

Original language	English
Title of host publication	AIP Conference Proceedings
Publisher	American Institute of Physics Inc.
Volume	1648
ISBN (Print)	9780735412873
DOIs	https://doi.org/10.1063/1.4912818
Publication status	Published - 2015 Mar 10
Event	International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 - Rhodes, Greece Duration: 2014 Sept 22 → 2014 Sept 28

Other

Other	International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
Country/Territory	Greece
City	Rhodes
Period	14/9/22 → 14/9/28

Keywords

Interaction
Lévy-walk
Multi-agent model
Power-law
Random Walk

ASJC Scopus subject areas

Physics and Astronomy(all)

Access to Document

10.1063/1.4912818

Cite this

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title = "Modulation effect with global ambiguity in 2-dimensional random walk",

abstract = "Here, we developed 2-dimensional multi agent random walk algorithm. In our algorithm, agents interact with each other and change their directional rules by detecting other agents' moving direction locally. In addition to that, modulation effects in which agents control rule intervals depending on amount of local other agents are equipped to our model. We show that modulation effects which introduce global ambiguity play a crucial role to establish optimal random walk by checking the slope value (μ) depending on dense of agents. We set modulation-added model and non-modulation model. The latter is control model. In case of non-modulation model, the slope values (μ) highly depends on dense of agents. However, in case of modulation-added model, the slope values (μ) are flexible and independent from dense of agents.",

keywords = "Interaction, L{\'e}vy-walk, Multi-agent model, Power-law, Random Walk",

author = "Tomoko Sakiyama and Yukio Gunji",

year = "2015",

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doi = "10.1063/1.4912818",

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volume = "1648",

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AU - Sakiyama, Tomoko

AU - Gunji, Yukio

PY - 2015/3/10

Y1 - 2015/3/10

N2 - Here, we developed 2-dimensional multi agent random walk algorithm. In our algorithm, agents interact with each other and change their directional rules by detecting other agents' moving direction locally. In addition to that, modulation effects in which agents control rule intervals depending on amount of local other agents are equipped to our model. We show that modulation effects which introduce global ambiguity play a crucial role to establish optimal random walk by checking the slope value (μ) depending on dense of agents. We set modulation-added model and non-modulation model. The latter is control model. In case of non-modulation model, the slope values (μ) highly depends on dense of agents. However, in case of modulation-added model, the slope values (μ) are flexible and independent from dense of agents.

AB - Here, we developed 2-dimensional multi agent random walk algorithm. In our algorithm, agents interact with each other and change their directional rules by detecting other agents' moving direction locally. In addition to that, modulation effects in which agents control rule intervals depending on amount of local other agents are equipped to our model. We show that modulation effects which introduce global ambiguity play a crucial role to establish optimal random walk by checking the slope value (μ) depending on dense of agents. We set modulation-added model and non-modulation model. The latter is control model. In case of non-modulation model, the slope values (μ) highly depends on dense of agents. However, in case of modulation-added model, the slope values (μ) are flexible and independent from dense of agents.

KW - Interaction

KW - Lévy-walk

KW - Multi-agent model

KW - Power-law

KW - Random Walk

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M3 - Conference contribution

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BT - AIP Conference Proceedings

PB - American Institute of Physics Inc.

T2 - International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014

Y2 - 22 September 2014 through 28 September 2014

ER -

Modulation effect with global ambiguity in 2-dimensional random walk

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